Correspondences lie at the heart of traditional non-rigid reconstruction [1]}, which is overlooked in the current image-based evaluation.
We propose to evaluate 2D correspondences across training frames with the percentage of correctly transferred keypoints (PCK-T) [2]}, which directly evaluates the quality of the inferred deformation.
Specifically, we sparsely annotate 2D keypoints across input frames to ensure that each keypoint is fully observed during training.
For correspondence readout from existing methods, we use either root finding [3]} or scene flow chaining. Please see the Appendix for details on our keypoint annotation, correspondence readout, and metric computation.
As shown in Figure REF , evaluating correspondences reveal that high quality image rendering does not necessarily result in accurate correspondences, which indicates issues in the underlying surface, due to the ambiguous nature of the problem.
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